}
    }

    /**
     * Sets the thread pool for executing the request.
     *
     * @param threadPool the thread pool
     * @return this CurlRequest instance
     */
    public CurlRequest threadPool(final ForkJoinPool threadPool) {
        this.threadPool = threadPool;
        return this;
    }

    /**
     * Sets the connection and read timeouts for the request.
     *

        To be awaitable, compatible with async, this is run in threadpool.
        """
        return await super().seek(offset)

    async def close(self) -> None:
        """
        Close the file.

        To be awaitable, compatible with async, this is run in threadpool.
        """
        return await super().close()

    @classmethod

   * be a SynchronousQueue.
   */
  private ExecutorService threadPool;

  @Override
  public void setUp() {
    threadPool = newCachedThreadPool();
  }

  @Override
  public void tearDown() throws InterruptedException {
    threadPool.shutdown();
    assertTrue("Some worker didn't finish in time", threadPool.awaitTermination(10, SECONDS));
  }

  private static <T> int drain(

    int deltaRange = 10000;
    String key = "key";

    AtomicLongMap<String> map = AtomicLongMap.create();

    ExecutorService threadPool = newFixedThreadPool(nThreads);
    ArrayList<Future<Long>> futures = new ArrayList<>();
    for (int i = 0; i < nTasks; i++) {
      futures.add(
          threadPool.submit(
              new Callable<Long>() {
                @Override
                public Long call() {

    int deltaRange = 10000;
    String key = "key";

    AtomicLongMap<String> map = AtomicLongMap.create();

    ExecutorService threadPool = newFixedThreadPool(nThreads);
    ArrayList<Future<Long>> futures = new ArrayList<>();
    for (int i = 0; i < nTasks; i++) {
      futures.add(
          threadPool.submit(
              new Callable<Long>() {
                @Override
                public Long call() {

  // TODO(b/113217601): This is needed for EagerContext::runner_ to use a
  // threadpool, so that we avoid the possibility of running the runner_ in the
  // threadpool of GPU event mgr, as that can trigger more callbacks to be
  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback

///

### Path operation functions { #path-operation-functions }

When you declare a *path operation function* with normal `def` instead of `async def`, it is run in an external threadpool that is then awaited, instead of being called directly (as it would block the server).

        ForkJoinPool pool = new ForkJoinPool(1);
        req.threadPool(pool);

        // ## Act ##
        // execute() should force synchronous execution but restore threadPool afterward
        try (CurlResponse response = req.execute()) {
            assertEquals(200, response.getHttpStatusCode());
        }

        // ## Assert ##
        // After execute(), the threadPool should be restored

    ExecutorService threadPool = newFixedThreadPool(nThreads);
    CountDownLatch tasksFinished = new CountDownLatch(nTasks);
    for (int i = 0; i < nTasks; i++) {
      String s = "a" + i;
      @SuppressWarnings("unused") // https://errorprone.info/bugpattern/FutureReturnValueIgnored
      Future<?> possiblyIgnoredError =
          threadPool.submit(
              () -> {

    ExecutorService threadPool = newFixedThreadPool(nThreads);
    CountDownLatch tasksFinished = new CountDownLatch(nTasks);
    for (int i = 0; i < nTasks; i++) {
      String s = "a" + i;
      @SuppressWarnings("unused") // https://errorprone.info/bugpattern/FutureReturnValueIgnored
      Future<?> possiblyIgnoredError =
          threadPool.submit(
              () -> {